## Using `diagnosis_date` as index variable.
## `summarise()` has grouped output by 'diagnosis_date'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'diagnosis_date'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'diagnosis_date', 'Postcode'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'diagnosis_date', 'Postcode', 'Localgovernmentarea'. You can override using the `.groups` argument.
## # A tibble: 10 × 2
##    agegroup total
##    <chr>    <int>
##  1 20-29     4434
##  2 30-39     3298
##  3 40-49     2357
##  4 10-19_    1959
##  5 50-59     1942
##  6 0-9       1178
##  7 60-69     1074
##  8 80-89     1053
##  9 70-79      785
## 10 90+        732

## Rows: 45862 Columns: 6
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (2): location, variant
## dbl  (3): num_sequences, perc_sequences, num_sequences_total
## date (1): date
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

Now, we analyze the corona virus variants in Turkey. The first and basic visualisation to check the distribution of the variants is a bar plot. The variants are plotted on a bar chart and we find that the delta variant is the most common infection in Turkey. “The Delta variant is a variant of concern that WHO is tracking and monitoring around the world. It’s a variant of concern because we know it has increased transmissibility. This has been demonstrated by several countries. And we know that where the Delta variant is identified, it really rapidly takes off and spreads between people more efficiently than even the Alpha variant that was first detected around December, January 2021. As of today, the Delta variant has been reported in 96 countries and we expect that the Delta variant will continue to spread.” ~ Dr Maria Van Kerkhove

Now, the first occurrence of the delta strain is identified and its relation with the increase in the number of cases will be discussed. The spread of the delta variant is super fast and it is proved by data in the plot below. The first occurence the delta variant in Turkey was in May 2021. The spread of it is so fast that, in August almost all of the cases are attributed to the delta variant.

Thus in all, I would say that the vaccination rate causes the infection rate to slow down. However, the neglected attitude of people and the hesitancy to take the vaccine has caused this pandemic to disturb normal life for longer times. The restrictions and other regulations have most definitely allowed us this time to face this pandemic in a stringer manner to avoid more deaths. Therefore, please get vaccinated and stay safe.

1

## `summarise()` has grouped output by 'month'. You can override using the `.groups` argument.
## Links is a tbl_df. Converting to a plain data frame.

Comparing Causes of Deaths in each Month

2

## Joining, by = c("POSTCODE", "PFI", "PFI_CR", "UFI", "UFI_CR", "UFI_OLD")
## Joining, by = c("NAME1", "UFI", "PFI", "FTYPE_CODE", "LGA_CODE", "NAME", "OFFICIALNM", "STATE", "ABSLGACODE", "NFEAT_ID", "FQID", "CRDATE_PFI", "SUPER_PFI", "CRDATE_UFI")
## Rows: 19 Columns: 98
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (98): SA4_CODE_2016, P_PGrad_Deg_35_44, P_PGrad_Deg_45_54, P_PGrad_Deg_5...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Rows: 19 Columns: 201
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (201): SA4_CODE_2016, M_Ag_For_Fshg_15_19, M_Ag_For_Fshg_20_24, M_Ag_For...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Rows: 19 Columns: 201
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (201): SA4_CODE_2016, M_Tot_15_19, M_Tot_20_24, M_Tot_25_34, M_Tot_35_44...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Rows: 19 Columns: 201
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (201): SA4_CODE_2016, F_ID_NS_15_19, F_ID_NS_20_24, F_ID_NS_25_34, F_ID_...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## `summarise()` has grouped output by 'SA4_CODE_2016'. You can override using the `.groups` argument.
## Joining, by = "SA4_CODE_2016"
## Warning in st_point_on_surface.sfc(sf::st_zm(x)): st_point_on_surface may not
## give correct results for longitude/latitude data
## Warning: Removed 2 rows containing missing values (geom_text).

3

## Warning: ggrepel: 4 unlabeled data points (too many overlaps). Consider
## increasing max.overlaps